There are huge growth projections for the AMR market.
Do you share this outlook and, if so, why?
We no longer use the terms AGV and AMR but collectively refer to all vehicles as mobile robots. That’s because, apart from minute details, these robots have almost identical capabilities regardless of their designation.
Automation based on mobile robots certainly is a trend right now and there are a number of reasons for that:
We have observed an increase in both the number of project inquiries and the complexity of these projects. The implementation of large lighthouse projects in the recent past has built confidence in the technology, which is a key growth factor.
What is the status quo of mobile robotics adoption in SMEs and how can SMEs benefit from this technology?
The technology is already making its mark in SMEs. We have implemented numerous projects in SMEs and successfully automated processes with small numbers of robots. In April, we established a partnership with TRUMPF to make mobile robot deployment more attractive to SMEs in sheet metal processing using a special material flow software. And we are involved in a research project at Rosenheim Technical University of Applied Sciences that follows a similar approach for wood-working companies. SMEs also need opportunities to benefit from advances in automation.
What is the potential impact of AI on the use or application areas of mobile robotics?
AI does not yet play any significant role in creating process descriptions, robot configurations, or navigation. Right now, there is simply not enough data and the algorithms are not sufficiently trained to be of much help in performing these tasks. Robot manufacturers need to develop and train their own encapsulated Artificial Intelligence over the next few years in an effort to unlock the use of AI in layout development or commissioning.
Creating or editing requirements specifications is another conceivable area of use, which, however, requires training as well.
Generative AI models such as ChatGPT do not have the data basis required to produce reliable results and should generally not be used for safety reasons.
SAFELOG continues to rely on human intelligence. It is not yet possible to integrate AI with smart algorithms based on years of project experience.
While it is certainly possible to speed up and simplify some workflows, I do not see any widespread adoption at this point.